As shown in Table REF , Joint Representation Learning (JRL) is the main adaptation driver, responsible for driving the student's latent space to represent different tasks. Furthermore, as we are using the same architecture for the teachers and students, the difference between \(\alpha = 1.0\)  and \(\alpha = 0.5\)  is not that significant here but immensely important when dealing with entire heterogeneous structures, as noted by [1]}. When JRL is disabled, the model has difficulties learning high-feature representations only with the soft domain adaptation (SDA), resulting in tremendous catastrophic forgetting.
